1. Technical Field
The invention relates to image processing. In particular, the invention relates to skin detection and localization in an image.
2. Related Art
Continuous and rapid developments in imaging technology have produced correspondingly greater demands on image processing systems. Extensive improvements in imaging technology have given rise to larger and higher resolution image data sets, which in turn require faster and more efficient processing systems to maintain an acceptable level of system responsiveness. At the same time, an increasing number of industries, ranging from security to medicine to manufacturing, have turned to image processing to keep pace with the demands of modern marketplaces.
For example, image processing to detect skin is an important first step in many security industry applications, including facial recognition and motion tracking. In the case of facial recognition, before a security application can compare a face to the faces in a database, an image processing system must first determine whether or not a video or static image even contains skin. If the image does contain skin, the image processing system must determine where in that image the skin is located and whether it is facial skin. Furthermore, it is often desirable to perform such skin and face detection in real-time to analyze, for example, a video stream running at 30 frames-per-second from a security camera.
In the past, a general purpose central processing unit (CPU) in an image processing system performed skin detection. Alternatively, costly and highly customized image processing hardware was sometimes designed and built to specifically detect skin in images. However, annual incremental advancements in general purpose CPU architectures do not directly correlate with an increased ability to perform specialized image processing functions such as skin detection and localization. Furthermore, the resources which a CPU may devote to skin detection are limited because the CPU must also execute other demanding general purpose system applications (e.g., word processors, spreadsheets, and computer aided design programs).
Therefore, past implementations of skin detection and localization were limited to two relatively unsatisfactory options: reduced speed and efficiency of processing performed by a general purpose CPU, or the increased costs and complexity of highly customized hardware. For example, designing and manufacturing highly customized hardware for skin detection to accommodate the massive rollout of security cameras throughout major cities, or the increased security screening at airports, would prove extremely costly and impractical. Yet these and other applications are limited in effectiveness without high performance image processing solutions.
Therefore, a need exists for an improved processing system for skin detection and localization.